Modeling the Processing of Non-Poissonian IIoT Traffic by Intra-Chip Routers of Network Data Processing Devices

The ecosystem of the Internet of Things (IoT) continues growing now and covers more and more fields. One of these areas is the Industrial Internet of Things (IIoT) which integrates sensors and actuators, business applications, open web applications, multimedia security systems, positioning, and tracking systems. Each of these components creates its own data stream and has its own parameters of the probability distribution when transmitting information packets. One such distribution, specific to the TrumpfTruPrint 1000 IIoT system, is the beta distribution. We described issues of the processing of such a data flow by an agent model of the $5\times5$ NoC switch fabric. The concepts of modern telecommunication networks 5G/6G imply the processing of “small” data in the place of their origin, not excluding the centralized processing of big data. This process, which involves the transmission, distribution, and processing of data, involves a large number of devices: routers, multiprocessor systems, multi-core systems, etc. We assumed that the data stream is processed by a device with the network structure, such as NoC, and goes to its built-in router. We carried out a study how the average queues of the $5\times5$ router change with changes in the parameters of a data stream that has a beta distribution.